code: def test_predict(self):
      model = EncoderDecoderRecognizer(
          decoder=dict(type="DummyModule", value=1)
      )
      self.assertEqual(
          model.predict(torch.tensor([1]), None), torch.Tensor([1])
      )
      model = EncoderDecoderRecognizer(
          encoder=dict(type="DummyModule", value=2),
          decoder=dict(type="DummyModule", value=1),
      )
      self.assertEqual(
          model.predict(torch.tensor([1]), None), torch.Tensor([4])
      )
      model = EncoderDecoderRecognizer(
          backbone=dict(type="DummyModule", value=1),
          encoder=dict(type="DummyModule", value=2),
          decoder=dict(type="DummyModule", value=1),
      )
      self.assertEqual(
          model.predict(torch.tensor([1]), None), torch.Tensor([6])
      )
      model = EncoderDecoderRecognizer(
          backbone=dict(type="DummyModule", value=1),
          decoder=dict(type="DummyModule", value=1),
      )
      self.assertEqual(
          model.loss(torch.tensor([1]), None), torch.Tensor([2])
      )
  
file_path: mmocr/tests/test_models/test_textrecog/test_recognizers/test_encoder_decoder_recognizer.py
imports: from unittest import TestCase
  import torch
  from mmocr.models.textrecog.recognizers import EncoderDecoderRecognizer
  from mmocr.registry import MODELS
label_desc: Use image node_id 4 for calling the TestEncoderDecoderRecognizer obj's underlying member method code with example usage: obj.test_predict() without return types